In this paper, we propose a novel deep neural network based on learning subspaces and convolutional neural network with applications in image classification ...
In this paper, we propose a novel deep neural net- work based on learning subspaces and convolutional neural network with applications in image classifica-.
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A semi-supervised convolutional neural network based on subspace representation for image classification. BB Gatto, LS Souza, EM dos Santos, K Fukui, WS S.
The authors in [59] proposed a deep learning approach by combining subspace feature extraction and CNNs for hyperspectral image classification. There were ...
A novel deep neural network based on learning subspaces and convolutional neural network with applications in image classification.
This paper proposes a new method to address these issues. The proposed method synergistically integrates model-based and data-driven learning in three key ...
Missing: approach classification.
In this paper, we propose a self-representative feature extraction deep neural network for unsupervised subspace clustering to improve representativeness and ...
We propose a novel SLM method that adopts soft partitioning, denoted as SLM/SP, to address the limitation. Our motivation is to develop a more efficient and ...
Oct 22, 2024 · Recent deep learning-based reconstruction methods promise to produce even higher quality reconstructions by utilizing more specific image priors ...
A Novel Deep Learning Framework by Combination of Subspace-Based Feature Extraction and Convolutional Neural Networks for Hyperspectral Images Classification.